In this paper, expressions for various measures of the probability of success are presented by type of endpoints. The discussion in this paper is restricted to the normally distributed test statistics along with normal prior, and beta prior for binomial distributions. For other distributions, the relevant expressions can be obtained using the general framework presented in Section  or simulation based methods such as Bayesian clinical trial simulation (BCTS) [1]}, [2]} may be used. Nevertheless, a natural question arises which pr(success) measure one should prefer. Often PPoS is preferred over CP for the following reasons: (1) these have better predictive interpretation, (2) unlike frequentist counterpart, the knowledge on \(\theta \)  (the parameter of interest) is used as distribution, whereas in frequentist calculation, we assume that the value of \(\theta \)  is known without any uncertainty, and (3) unlike frequentist paradigm, the prior information can be incorporated in the Bayesian paradigm. As evident from Figure REF , Figure REF  and Figure REF , the CP is more aggressive than the PPoS and hence use of the CP increases the chance of early stopping for futility or efficacy. [3]} has shown that futility termination may markedly decrease the power in direct proportion to the probability of stopping for futility. Therefore, PPoS seems to be more useful while monitoring a trial for early termination.
